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Sedentary behaviors such as sitting and watching TV are ubiquitous in modern societies. Increases in sedentary time have been linked with an increased risk of obesity, diabetes, cardiovascular disease, and all-cause mortality. While smartphones and wearables can now detect sedentary user behaviors, few computational models exist for predicting when they will occur in future. In this paper, we propose...
Sedentary lifestyles are ubiquitous in modern societies. Watching television, playing video games, and using the computer while sitting are examples of sedentary behaviors that are now common worldwide. Multiple research studies have found that the length of sedentary time is linked with an increased risk of obesity, diabetes, cardiovascular disease, and all-cause mortality. Medical researchers have...
Sedentary behaviors such as sitting and watching TV increase the risk of many ailments including diabetes, cardiovascular disease and all-cause mortality. Fitness trackers and smartphone apps automatically track users' physical activities and sedentary behaviors to support self-monitoring. These trackers generate activity time-series data that require manual analysis to detect recurrent patterns....
The evaluation of biometric sample quality is of great importance in the evaluation of biometric algorithms. In this paper, we propose a novel hierarchical model to compute the sample quality at three levels. This model is developed on the basis of three types of influencing factors: global factors, subjective factors and variable factors. We adopt different strategies to compute the corresponding...
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